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Record W4293074014 · doi:10.11159/iccste22.117

Inelastic Behavior of Thin-walled Circular Steel Tubular Columns Under Pushover and Cyclic Loading

2022· article· en· W4293074014 on OpenAlexvenueno aff
Njiru Mwaura, Iraj H. P. Mamaghani

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringMaterials scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

Thin-walled circular steel tubular columns have been used as bridge piers widely around the globe because of their excellent seismic performance: ductility, strength, and energy dissipation capacity. This paper investigates the inelastic behavior of thin-walled circular steel tubular columns with a uniform cross-section. The loading protocol considered for this study is either pushover or cyclic lateral loading in the presence of a constant axial load. The effects of a pushover and cyclic lateral loading on the behavior of the thinwalled circular steel tubular columns modeling bridge piers have been evaluated through analysis of failure mode, hysteresis curve, envelope curve, stiffness, and strength degradation characteristics, including pre-and post-buckling regimes. The study applies the finite element model (FEM) that considers the effect of both material and geometric nonlinearities. Also, in an accompanying paper, a comprehensive parametric study was carried out to investigate the effects of the critical design parameters and namely are: the radius to thickness parameter (Rt), the column slenderness ratio parameter (), and the magnitude of axial load (P/Py). Finally, a series of proposed formulae for strength and ductility evaluation for thin-walled circular steel tubular columns are given.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.206
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

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